SYSTEM AND METHOD FOR AI-BASED ANTI-FRAUD USER TRAINING AND PROTECTION

摘要

A new approach is proposed to support anti-fraud user training and protection by identifying and training individuals within an entity who are at high risk of being targeted in an impersonating attack. An AI engine automatically collects historical electronic messages of each individual in the entity on an electronic messaging system via an application programming interface (API) call. The AI engine then analyzes contents the collected historical electronic messages and calculates a security score for each individual via AI-based classification. The AI engine identifies high-risk individuals within the entity based on their security scores and launches simulated impersonating attacks against these individuals to test their security awareness. The AI engine then collects and analyzes responses to the simulated attacks by those high-risk individuals in real time to identify issues in the responses and to take corresponding actions to prevent the high-risk individuals from suffering damages in case of real attacks.